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A Kalman filter algorithm for identifying track irregularities of railway bridges using vehicle dynamic responses

机译：利用车辆动态响应识别铁路桥梁轨道不平顺的卡尔曼滤波算法

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摘要

Track irregularities affect the running safety of railway vehicles and ride comfort, hence track irregularity identification using the dynamic responses of in-service vehicles is of great interest. Because the high-speed rail lines mainly consist of bridges in China, vehicle-bridge (VB) interactions which significantly influence the vehicle dynamic responses should be taken into account in the track irregularity identification. This paper proposes a Kalman filter algorithm to identify the track irregularities of railway bridges using vehicle dynamic responses considering the VB interactions in real-time. A state space model is established to represent a time-dependent VB system subjected to unknown track irregularity excitations. A Kalman filter algorithm is proposed to estimate optimally the state vector of the VB system and to identify the track irregularities subsequently. Two numerical examples including a real railway bridge constructed in China are presented to validate the accuracy of the proposed algorithm. A parametric study is also conducted to demonstrate the effects of measurement noise, vehicle running state, parameter uncertainty and model uncertainty on the identification of track irregularities. Comparison results demonstrate that the proposed track irregularity identification algorithm outperforms the conventional approaches mainly because of considering the VB interaction. The proposed algorithm enables efficient monitoring the track irregularities of railway bridges using the acceleration responses of in-service vehicles.
机译：轨道不平整会影响铁路车辆的行驶安全性和乘坐舒适性，因此，使用在役车辆的动态响应来识别轨道不平整非常重要。在中国，由于高速铁路主要由桥梁组成，因此在轨道不平顺识别中应考虑对车辆动态响应有重大影响的车桥（VB）相互作用。本文提出了一种卡尔曼滤波算法，利用车辆动态响应实时考虑VB相互作用，识别铁路桥梁的轨道不平顺性。建立状态空间模型来表示受到未知磁道不规则性激励的时间相关的VB系统。提出了一种卡尔曼滤波算法，以最优地估计VB系统的状态向量，并随后识别出轨道不规则性。给出了两个数值示例，包括在中国建造的实际铁路桥梁，以验证所提出算法的准确性。还进行了参数研究，以证明测量噪声，车辆行驶状态，参数不确定性和模型不确定性对识别轨道不规则性的影响。比较结果表明，提出的轨道不规则性识别算法优于常规方法，主要是因为考虑了VB交互作用。所提出的算法能够利用在役车辆的加速度响应来有效地监测铁路桥梁的轨道不平顺性。

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